A systematic literature review on software defect prediction using artificial intelligence: Datasets, Data Validation Methods, Approaches, and Tools
Delivering high-quality software products is a challenging task. It needs proper coordination
from various teams in planning, execution, and testing. Many software products have high …
from various teams in planning, execution, and testing. Many software products have high …
Progress on approaches to software defect prediction
Software defect prediction is one of the most popular research topics in software
engineering. It aims to predict defect‐prone software modules before defects are discovered …
engineering. It aims to predict defect‐prone software modules before defects are discovered …
Heterogeneous defect prediction
Software defect prediction is one of the most active research areas in software engineering.
We can build a prediction model with defect data collected from a software project and …
We can build a prediction model with defect data collected from a software project and …
A consolidated decision tree-based intrusion detection system for binary and multiclass imbalanced datasets
The widespread acceptance and increase of the Internet and mobile technologies have
revolutionized our existence. On the other hand, the world is witnessing and suffering due to …
revolutionized our existence. On the other hand, the world is witnessing and suffering due to …
Perceptions, expectations, and challenges in defect prediction
Defect prediction has been an active research area for over four decades. Despite
numerous studies on defect prediction, the potential value of defect prediction in practice …
numerous studies on defect prediction, the potential value of defect prediction in practice …
How far we have progressed in the journey? an examination of cross-project defect prediction
Background. Recent years have seen an increasing interest in cross-project defect
prediction (CPDP), which aims to apply defect prediction models built on source projects to a …
prediction (CPDP), which aims to apply defect prediction models built on source projects to a …
Feature selection for imbalanced data based on neighborhood rough sets
H Chen, T Li, X Fan, C Luo - Information sciences, 2019 - Elsevier
Feature selection is a meaningful aspect of data mining that aims to select more relevant
data features and provide more concise and explicit data descriptions. It is beneficial for …
data features and provide more concise and explicit data descriptions. It is beneficial for …
Seml: A semantic LSTM model for software defect prediction
H Liang, Y Yu, L Jiang, Z **e - IEEE Access, 2019 - ieeexplore.ieee.org
Software defect prediction can assist developers in finding potential bugs and reducing
maintenance cost. Traditional approaches usually utilize software metrics (Lines of Code …
maintenance cost. Traditional approaches usually utilize software metrics (Lines of Code …
Performance analysis of feature selection methods in software defect prediction: a search method approach
Software Defect Prediction (SDP) models are built using software metrics derived from
software systems. The quality of SDP models depends largely on the quality of software …
software systems. The quality of SDP models depends largely on the quality of software …
Incremental weighted ensemble broad learning system for imbalanced data
Broad learning system (BLS) is a novel and efficient model, which facilitates representation
learning and classification by concatenating feature nodes and enhancement nodes. In spite …
learning and classification by concatenating feature nodes and enhancement nodes. In spite …